Per Capita Cases By County

Data Updated as of June 30, 2020

Data Sources: Johns Hopkins University Center for Systems Science and Engineering, USAFacts, American Community Survey 2018 (5-Year Estimates)
Note: Does not include cases not assigned to counties.

Social Risk Factors By County

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Data Sources: Johns Hopkins University Center for Systems Science and Engineering, USAFacts, American Community Survey 2018 (5-Year Estimates), County Health Rankings, Homeland Infrastructure Foundation-Level Data
Note: Does not include cases not assigned to counties.

Preliminary Analysis

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Regression Model

Fixed Effects Model of Covid-19 Deaths per Capita in U.S. Counties, January 22 - June 30
Dependent variable:
Deaths per Capita
Population Density 0.22*** (0.02)
% 65 and Above 0.01 (0.02)
% Black 0.33*** (0.03)
% Hispanic 0.05* (0.03)
Median Income 0.08** (0.03)
Gini Index (Economic Inequality) 0.04* (0.02)
Black-White Dissimilarity Index 0.05** (0.02)
Black-White Interaction Index -0.05* (0.02)
% College Degree -0.06* (0.03)
% Living in Correctional Facility -0.03* (0.02)
% Living in Nursing Home 0.10*** (0.02)
% Obese 0.01 (0.03)
% Without Health Insurance 0.08* (0.03)
Primary Care Doctors 0.01 (0.02)
Hospital Beds -0.03 (0.02)
Religious Organizations -0.06** (0.02)
Civic Organizations -0.06** (0.02)
Parks 0.02 (0.02)
Service Orgs Focused on Elderly/Disabled -0.02 (0.02)
State Fixed Effects? Yes
Observations 3,132
R2 0.19
Adjusted R2 0.17
F Statistic 36.64***
Note: Variables are population weighted and scaled, with a mean of 0 and standard deviation of 1.
***: p<0.001; **: p<0.01; *: p<0.05

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Coefficients Plot

Notes: Unit of analysis: U.S. counties.
Only statistically significant variables at the .05 level are included in the coefficient plot. Other variables can be found in the table to the left.
Bands are 95% confidence intervals.

Analysis Details

Data Sources

Data for the analysis come from various sources.

Cases and Deaths

Confirmed cases and deaths come from USAFacts, which collect the data from state and local agencies. The number of viral tests given, at the state level, come from the COVID Tracking Project, but they are not included in the analysis (see below).

Demographic and Socioeconomic Indicators

Demographic and socioeconomic indicators – including total population, racial and ethnic makeup, income measures (both median income and income inequality), and education levels – all come from five-year estimates from the Census Bureau’s 2014-2018 American Community Survey. Data for number of people living in correctional facilities and nursing homes come from the 2010 Decennial Census.

Health indicators

Health indicators – the number of people that are obese, the number without health insurance, and the number of primary care physicians – come from the County Health Rankings. The number of hospital beds comes from the Homeland Infrastructure Foundation-Level Data.

Social and Civic Infrastructure

Methods

The analysis on the previous page is a regression of Covid-19 deaths per capita in the U.S. on a number of demographic, social, and economic indicators – all measured at the county level. I include state fixed effects, which tries to account for the fact that counties within a state have similar characteristics, including, in this case, state wide stay-at-home orders. Running the analysis without state fixed effects and including state-level viral testing capacity (which can’t be included in the fixed effects model) doesn’t substantively change the findings.

Segregation Indices

The formula for the Black-White dissimilarity index, for each county, is:

\[\frac{1}{2} * \sum_{i}^{n}\left|\frac{b_{i}}{B}-\frac{w_{i}}{W}\right|\] where \(b_{i}\) is the Black population in \(i\) Census Tract, \(B\) is the total Black population in the county, \(w_{i}\) is the White population in \(i\) Census Tract, and \(W\) is the total White population in the county.

The formula for the Black-White interaction index, for each county, is:

\[\sum_{i}^{n}\left[\frac{b_{i}}{B}*\frac{w_{i}}{t_{i}}\right]\] where all measures are the same as in the dissimilarity index, except that \(t_{i}\) is the total population of the Census Tract.